Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
#load data
df = px.data.gapminder()
df.head()
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
Recreate the barplot below that shows the population of different continents for the year 2007.
Hints:
df_2007 = df.query('year==2007')
df_2007_new = df_2007.groupby('continent').sum()
fig=px.bar(df_2007_new, x='pop', y=df_2007_new.index, color=['Africa', 'Americas', 'Asia', 'Europe', 'Oceania'])
fig.show()
df_2007 = df.query('year==2007')
df_2007_new = df_2007.groupby('continent').sum().sort_values('pop', ascending=True)
fig=px.bar(df_2007_new, x='pop', y=df_2007_new.index, color=['Oceania', 'Europe', 'Americas', 'Africa', 'Asia'],
)
fig.show()
Add text to each bar that represents the population
df_2007 = df.query('year==2007')
df_2007_new = df_2007.groupby('continent').sum().sort_values('pop', ascending=True)
fig=px.bar(df_2007_new, x='pop', y=df_2007_new.index, color=['Oceania', 'Europe', 'Americas', 'Africa', 'Asia'],
text_auto=True)
fig.show()
Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years
df = px.data.gapminder()
fig = px.histogram(df,
x="pop",
y="continent",
animation_frame="year",
color="continent", range_x=[0,4000000000])
fig.show()
Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years
df = px.data.gapminder()
fig = px.histogram(df,
x="pop",
y="country",
animation_frame="year",
color="continent", range_x=[0,1400000000]).update_yaxes(categoryorder="total ascending")
fig.update_layout(xaxis_title = 'pop')
fig.show()
Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation
df = px.data.gapminder()
fig = px.histogram(df, x="pop", y="country", animation_frame="year",
color="continent", range_x=[0,1400000000]).update_yaxes(categoryorder="total ascending")
fig.update_layout(xaxis_title = 'pop', showlegend = False, autosize = False, width=1000, height=1000)
fig.show()
df = px.data.gapminder()
fig = px.histogram(df, x="pop", y="country", animation_frame="year",
color="continent", range_x=[0,1400000000],range_y = [131.5, 141.5]).update_yaxes(categoryorder="total ascending")
fig.update_layout(xaxis_title = 'pop', showlegend = False, autosize = False, width=1000, height=1000)
fig.show()